Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Journal of Applied Sciences
  Year: 2012 | Volume: 12 | Issue: 19 | Page No.: 1995-2005
DOI: 10.3923/jas.2012.1995.2005
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

The Quantum Approach Leading from Evolutionary to Exhaustive Optimization

Massimo Panella and Giuseppe Martinelli

Abstract:
What bio-inspired algorithms mimic are natural mechanisms governing the macroscopic world for optimizing actual performances that are of vital importance. Neural and neurofuzzy networks, genetic, swarm-intelligence and other evolutionary algorithms are well-known results of this imitation. A completely different situation characterizes the microscopic world governed by quantum mechanics. All the possible solutions exist simultaneously in superposition and the problem is to extract the optimal one. In this case, basic mechanisms of quantum mechanics, i.e., superposition and entanglement, are necessary to mimic nature. Following the latter approach, in this paper a quantum architecture was proposed for determining the maximum/minimum in a set of positive integers which is a basic problem related to optimization. The proposed architecture is based on a suitable nonlinear quantum operator and it solves the said problem by an exhaustive search. This was illustrated in detail in the case of a typical NP-complete problem.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    A Novel Quantum-inspired Binary Gravitational Search Algorithm in Obtaining Optimal Power Quality Monitor Placement
How to cite this article:

Massimo Panella and Giuseppe Martinelli, 2012. The Quantum Approach Leading from Evolutionary to Exhaustive Optimization. Journal of Applied Sciences, 12: 1995-2005.

DOI: 10.3923/jas.2012.1995.2005

URL: https://scialert.net/abstract/?doi=jas.2012.1995.2005

COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 

Curve Bottom